Biology subjects

Horvath, J.

Publications and source records attributed to Horvath, J..

9 recordsLinked to original sources

bioRxiv2025

Lipid transport is necessary for neocortical lamination

We previously described the Alkuraya-Ku[c]inskas syndrome, a disorder associated with biallelic variants in BLTP1 (bridge-like lipid transfer protein), a.k.a. KIAA1109. The majority of probands die perinatally with corpus callosum agenesis, ventriculomegaly and arthrogryposis. Homozygous ablation of mouse Bltp1 resulted in similar preweaning lethality. Here, we describe ten novel patients expanding the characterization of this syndrome at the mild end of the phenotypic spectrum. To model this syndrome, we engineered Emx1-Cre-mediated conditional knockouts (cKO) in which Bltp1 expression is only removed in cortical and hippocampal neurons. This restricted ablation of Bltp1 recapitulated the preweaning lethality observed in the constitutional knockouts, suggesting that lack of BLTP1 expression in neurons is sufficient to cause death. Homozygous cKO presented a complete agenesis of the corpus callosum, a smaller anterior commissure, a malformed hippocampus and a reduced thickness of the cortical plate with a complete lack of defined structural layers and absence of radial glial and intermediate neural progenitors and mature neurons. As BLTP1 was shown to be a barrel-shaped tube containing lipids, we compared the amount of lipid species in the cKO and their control littermates cortexes. We observed significant depletions of ether-linked phosphatidylethanolamines and triglycerides and accumulations of sphingomyelins and hexosylceramides in cKOs. Our results are consistent with the recent description of BLTP1 as a tubular protein that transports phospholipids between the endoplasmic reticulum and the plasma membrane. They suggest that non-vesicular lipid transport is essential for neocortical and cerebellar lamination. Consistent with a BLTP1 role in cortex development we show that heterozygous carriers of a BLTP1 truncation variant presented a decrease in peripheral cortical grey matter suggesting an autosomal dominant inheritance pattern beside the already described autosomal recessive.

genetics↗

bioRxiv2024

Catalytic inhibition of KAT6/KAT7 enhances the efficacy and overcomes primary and acquired resistance to Menin inhibitors in MLL leukaemia

Understanding the molecular pathogenesis of MLL fusion oncoprotein (MLL-FP) leukaemia has spawned epigenetic therapies that have improved clinical outcomes in this often-incurable disease. Using genetic and pharmacological approaches, we define the individual and combined contribution of KAT6A, KAT6B and KAT7, in MLL-FP leukaemia. Whilst inhibition of KAT6A/B is efficacious in some pre-clinical models, simultaneous targeting of KAT7, with the novel inhibitor PF-9363, increases the therapeutic efficacy. KAT7 interacts with Menin and the MLL complex and is co-localised at chromatin to co-regulate the MLL-FP transcriptional program. Inhibition of KAT6/KAT7 provides an orthogonal route to targeting Menin to disable the transcriptional activity of MLL-FP. Consequently, combined inhibition rapidly evicts the MLL-FP from chromatin, potently represses oncogenic transcription and overcomes primary resistance to Menin inhibitors. Moreover, PF-9363 or genetic depletion of KAT7 can also overcome acquired genetic/non-genetic resistance to Menin inhibition. These data provide the molecular rationale for rapid clinical translation of combination therapy in MLL-FP leukaemia.

cancer biology↗

bioRxiv2024

A megatransposon drives the adaptation of Thermoanaerobacter kivui to carbon monoxide

Acetogens are promising industrial biocatalysts for upgrading syngas, a gas mixture containing CO, H2 and CO2 into fuels and chemicals. However, CO severely inhibits growth of many acetogens, often requiring extensive adaptation to enable efficient CO conversion ("carboxydotrophy"). Here, we adapted the thermophilic acetogen Thermoanaerobacter kivui to use CO as sole carbon and energy source. Isolate CO-1 exhibited extremely rapid growth on CO and syngas (co-utilizing CO, H2 and CO2) in batch and continuous cultures ({micro}max [~] 0.25 h-1). The carboxydotrophic phenotype was attributed to the mobilization of a CO-inducible megatransposon originating from the locus responsible for autotrophy in T. kivui. Transcriptomics illuminated the crucial role maintaining redox balance likely plays during carboxydotrophic growth. These novel insights were exploited to rationally engineer T. kivui to grow on CO. Collectively, our work elucidates a primary mechanism responsible for the acquisition of carboxydotrophy in homoacetogens and showcases how transposons can orchestrate evolution.

microbiology↗

bioRxiv2024

Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning.

BackgroundLong terminal repeats (LTRs) represent important parts of LTR retrotransposons and retroviruses found in high copy numbers in a majority of eukaryotic genomes. LTRs contain regulatory sequences essential for the life cycle of the retrotransposon. Previous experimental and sequence studies have provided only limited information about LTR structure and composition, mostly from model systems. To enhance our understanding of these key compounds, we focused on the contrasts between LTRs of various retrotransposon families and other genomic regions. Furthermore, this approach can be utilized for the classification and prediction of LTRs. ResultsWe used machine learning methods suitable for DNA sequence classification and applied them to a large dataset of plant LTR retrotransposon sequences. We trained three machine learning models using (i) traditional model ensembles (Gradient Boosting - GBC), (ii) hybrid CNN-LSTM models, and (iii) a pre-trained transformer-based model (DNABERT) using k-mer sequence representation. All three approaches were successful in classifying and isolating LTRs in this data, as well as providing valuable insights into LTR sequence composition. The best classification (expressed as F1 score) achieved for LTR detection was 0.85 using the CNN-LSTM hybrid network model. The most accurate classification task was superfamily classification (F1=0.89) while the least accurate was family classification (F1=0.74). The trained models were subjected to explainability analysis. SHAP positional analysis identified a mixture of interesting features, many of which had a preferred absolute position within the LTR and/or were biologically relevant, such as a centrally positioned TATA-box, and TG..CA patterns around both LTR edges. ConclusionsOur results show that the models used here recognized biologically relevant motifs, such as core promoter elements in the LTR detection task, and a development and stress-related subclass of transcription factor binding sites in the family classification task. Explainability analysis also highlighted the importance of 5- and 3-edges in LTR identity and revealed need to analyze more than just dinucleotides at these ends. Our work shows the applicability of machine learning models to regulatory sequence analysis and classification, and demonstrates the important role of the identified motifs in LTR detection.

bioinformatics↗

bioRxiv2023

The landscape of tolerated genetic variation in humans and primates

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole genome sequencing data for 809 individuals from 233 primate species, and identified 4.3 million common protein-altering variants with orthologs in human. We show that these variants can be inferred to have non-deleterious effects in human based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases. One Sentence SummaryDeep learning classifier trained on 4.3 million common primate missense variants predicts variant pathogenicity in humans.

genomics↗

bioRxiv2023

A global catalog of whole-genome diversity from 233 primate species

The rich diversity of morphology and behavior displayed across primate species provides an informative context in which to study the impact of genomic diversity on fundamental biological processes. Analysis of that diversity provides insight into long-standing questions in evolutionary and conservation biology, and is urgent given severe threats these species are facing. Here, we present high coverage whole-genome data from 233 primate species representing 86% of genera and all 16 families. This dataset was used, together with fossil calibration, to create a nuclear DNA phylogeny and to reassess evolutionary divergence times among primate clades. We found within-species genetic diversity across families and geographic regions to be associated with climate and sociality, but not with extinction risk. Furthermore, mutation rates differ across species, potentially influenced by effective population sizes. Lastly, we identified extensive recurrence of missense mutations previously thought to be human-specific. This study will open a wide range of research avenues for future primate genomic research. One-Sentence SummaryThe whole genome sequences of 233 primate species provide insight into the determinants of genetic diversity, phylogenomics, and human uniqueness.

genomics↗

bioRxiv2022

STAT3 restricts prostate cancer metastasis and antiandrogen resistance by controlling LKB1/CREB signaling pathway

Prostate cancer (PCa) lethality is driven by its progression to a metastatic castration-resistant state, yet the signaling mechanisms underlying metastatic spread remain unknown. Here we show that STAT3 converges with the LKB1/mTORC1 and CREB to control metastatic disease in PCa mouse models. Unexpectedly, STAT3 was found to be upregulated in diabetic PCa patients undergoing metformin therapy with a concomitant reduction in mTORC1 expression. In preclinical mouse models of PCa, genetic ablation or activation of STAT3 had opposing effects on LKB1/AMPK/mTORC1- dependent tumorigenesis. Using genetic and pharmacological approaches, we identified LKB1 as a direct STAT3 target while repressing CREB. Furthermore, PCa patients with high CREB expression had inferior clinical outcome with significantly increased risk of disease and metastatic recurrence. We observe that castration state lowers STAT3 abundance and increases AR and CREB levels, leading to castration-resistant PCa (CRPC). Our findings revealed that STAT3 controls mTORC1 and CREB in metastatic disease, suggesting CREB as a promising target for lethal CRPC.

cancer biology↗

bioRxiv2020

Sensorimotor hallucinationsin Parkinson's disease

Hallucinations in Parkinsons disease (PD) are one of the most disturbing non-motor symptoms, affect half of the patients, and constitute a major risk factor for adverse clinical outcomes such as psychosis and dementia. Here we report a robotics-based approach, enabling the induction of a specific clinically-relevant hallucination (presence hallucination, PH) under controlled experimental conditions and the characterization of a PD subgroup with enhanced sensorimotor sensitivity for such robot-induced PH. Using MR-compatible robotics in healthy participants and lesion network mapping analysis in neurological non-PD patients, we identify a fronto-temporal network that was associated with PH. This common PH-network was selectively disrupted in a new and independent sample of PD patients and predicted the presence of symptomatic PH. These robotics-neuroimaging findings determine the behavioral and neural mechanisms of PH and reveal pathological cortical sensorimotor processes of PH in PD, identifying a more severe form of PD associated with psychosis and cognitive decline.

neuroscience↗

bioRxiv2018

STAT3 promotes melanoma metastasis by CEBP-induced repression of the MITF pigmentation pathway

Metastatic melanoma is hallmarked by its ability to switch oncogenic MITF expression. Here we tested the impact of STAT3 on melanoma onset and progression in association with MITF expression levels. We established a mouse melanoma model for deleting Stat3 specifically in melanocytes with specific expression of human hyperactive NRASQ61K in an Ink4a deficient background. Mice with tissue specific Stat3 deletion showed an early onset of disease, but displayed significantly diminished lung metastases. Whole genome expression profiling also revealed a reduced invasion phenotype, which was functionally confirmed in 3D melanoma model systems. Notably, loss or knockdown of STAT3 in mouse or human cells resulted in up-regulation of MITF and induction of cell proliferation. Mechanistically we show that STAT3 induced CEBPa/b expression was sufficient to suppress MITF transcription. Epigenetic analysis by ATAC-seq confirmed that STAT3 enabled CEBPa/b binding to the MITF enhancer region thereby silencing it. We conclude that STAT3 is a metastasis driver in melanoma able to antagonize the MITF oncogene via direct induction of CEBP family member transcription facilitating RAS-RAF-driven melanoma metastasis.\n\nList of Abbreviations\n\nATAC-seq, Assay for Transposase-Accessible Chromatin using sequencing; CEBP, CAAT Box Enhancer Binding Protein; CRE, Cre recombinase; EGF, Epidermal Growth Factor; GEO, Gene Expression Omnibus; GSEA, Gene Set Enrichment Analysis; HSC70, Heat Shock 70 kDa protein; IHC, Immunohistochemistry; IL-6, Interleukin-6; JAK, Janus Kinase; MITF, Microphthalmia-Associated Transcription Factor; NSG, NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mice; OSM, Oncostatin M; PDGF, Platelet-Derived Growth Factor; pS, phosphoserine; pY, phosphotyrosine; RAS, Rat Sarcoma; RAF, Rapidly Accelerated Fibrosarcoma; RTK, Receptor Tyrosine Kinase; RT-PCR, Reverse Transcription Polymerase Chain Reaction; S100b, Calcium Binding Protein S100 beta; shRNA, short hairpin RNA; SOX10, Sex Determining Region Y-10; STAT, Signal Transducer and Activator of Transcription; TCGA, The Cancer Genome Atlas; TMA, Tissue Micro Array

cancer biology↗